Furthermore, evolutionary computation has demonstrated the capability of solving HPO problems [1]}, [2]}, [3]}, [4]}. CMA-ES [3]} imitates the biological evolution, assuming that no matter what kind of gene changes, the results (traits) always follow a Gaussian distribution of a variance and zero-mean. Meanwhile, the generated population is evaluated on the objective function, and a portion of the individuals with excellent performance is selected to suggest evolution, moving to the area where better individuals would be drawn with higher probability.
